修复了数据可视化字段匹配错误导致饼图生成错误的bug

elastic/es_connect.py

@@ -5,6 +5,8 @@ Django版本的ES连接和操作模块
 from elasticsearch import Elasticsearch
 from elasticsearch_dsl import connections
 import os
+import json
+import re
 from .documents import AchievementDocument, UserDocument, GlobalDocument
 from .indexes import ACHIEVEMENT_INDEX_NAME, USER_INDEX_NAME, GLOBAL_INDEX_NAME
 import hashlib
@@ -321,23 +323,45 @@ def _compute_hist(range_gte: str, interval: str, fmt: str):
     buckets = getattr(resp.aggs, 'b').buckets
     return [{"label": b.key_as_string, "count": b.doc_count} for b in buckets]
 
-def _compute_type_counts(range_gte: str, types: list):
-    counts = []
-    for t in types:
-        s = AchievementDocument.search()
-        s = s.filter('range', time={'gte': range_gte, 'lte': 'now'})
-        s = s.query('match_phrase', data=str(t))
-        total = s.count()
-        counts.append({"type": str(t), "count": int(total)})
-    return counts
+def _parse_type_from_data(data_str: str):
+    try:
+        obj = json.loads(data_str)
+        if isinstance(obj, dict):
+            for k in ("数据类型", "类型", "type"):
+                if k in obj and obj.get(k):
+                    return str(obj.get(k)).strip().strip(';')
+    except Exception:
+        pass
+    try:
+        m = re.search(r'"数据类型"\s*:\s*"(.*?)"', data_str)
+        if m:
+            return str(m.group(1)).strip().strip(';')
+    except Exception:
+        pass
+    return None
+
+def _compute_type_counts_dynamic(range_gte: str):
+    s = AchievementDocument.search()
+    s = s.filter('range', time={'gte': range_gte, 'lte': 'now'})
+    s = s.query('match_all')
+    counts_map = {}
+    for hit in s.scan():
+        t = _parse_type_from_data(getattr(hit, 'data', '') or '')
+        if not t:
+            continue
+        counts_map[t] = counts_map.get(t, 0) + 1
+        try:
+            ensure_type_in_list(t)
+        except Exception:
+            pass
+    return [{"type": k, "count": int(v)} for k, v in counts_map.items()]
 
 def compute_analytics():
-    types = get_type_list()
     days = _compute_hist('now-10d/d', 'day', 'yyyy-MM-dd')
     weeks = _compute_hist('now-10w/w', 'week', 'yyyy-ww')
     months = _compute_hist('now-10M/M', 'month', 'yyyy-MM')
-    pie_1m = _compute_type_counts('now-1M/M', types)
-    pie_12m = _compute_type_counts('now-12M/M', types)
+    pie_1m = _compute_type_counts_dynamic('now-1M/M')
+    pie_12m = _compute_type_counts_dynamic('now-12M/M')
     return {
         "last_10_days": days[-10:],
         "last_10_weeks": weeks[-10:],